A Novel Size-Based Centrifugal Microfluidic Design to Enrich and Magnetically Isolate Circulating Tumor Cells from Blood Cells through Biocompatible Magnetite–Arginine Nanoparticles
Bibliographic record
Abstract
This paper presents a novel centrifugal microfluidic approach (so-called lab-on-a-CD) for magnetic circulating tumor cell (CTC) separation from the other healthy cells according to their physical and acquired chemical properties. This study enhances the efficiency of CTC isolation, crucial for cancer diagnosis, prognosis, and therapy. CTCs are cells that break away from primary tumors and travel through the bloodstream; however, isolating CTCs from blood cells is difficult due to their low numbers and diverse characteristics. The proposed microfluidic device consists of two sections: a passive section that uses inertial force and bifurcation law to sort CTCs into different streamlines based on size and shape and an active section that uses magnetic forces along with Dean drag, inertial, and centrifugal forces to capture magnetized CTCs at the downstream of the microchannel. The authors designed, simulated, fabricated, and tested the device with cultured cancer cells and human cells. We also proposed a cost-effective method to mitigate the surface roughness and smooth surfaces created by micromachines and a unique pulsatile technique for flow control to improve separation efficiency. The possibility of a device with fewer layers to improve the leaks and alignment concerns was also demonstrated. The fabricated device could quickly handle a large volume of samples and achieve a high separation efficiency (93%) of CTCs at an optimal angular velocity. The paper shows the feasibility and potential of the proposed centrifugal microfluidic approach to satisfy the pumping, cell sorting, and separating functions for CTC separation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".